The Impact of AI on The Supply Chain Control Tower
Supply Chain Control Tower - a frequently used term that offers a lot of room for interpretation and various meanings. In this article we want to highlight what exactly the Supply Chain Control Tower is, what typical forms it takes and what the Control Tower of the future might look like.
The Control Tower as a Control Center
In general, the Supply Chain Control Tower is a concept that assumes a central control and monitoring instance of the logistics processes and provides an overview of all data and processes as a tool. The core of the concept is therefore to be able to retrieve and control all digital information. Often the control tower is also - hence its name - compared to an air traffic control tower, which always keeps track of air traffic movements on the ground and in the air. You can also think of the Control Tower as a large monitor that records all processes along the supply chain. Among others, the aim is to identify problems and supply bottlenecks at an early stage and to be able to act accordingly. In addition, weak points are identified and improved more quickly.
The basis for a functioning control tower is centralization of data. Data that can be used as a basis for analysis purposes. This includes transport data, current data on delivery stocks and transport costs. Existing applications such as ERP, WMS and TMS systems are integrated via a central system, making it possible to synchronize the relevant information and view it on a central platform. Suppliers, manufacturers and other cooperation partners can also be integrated. In this way, the Supply Chain Control Tower develops into an information network that can provide end-to-end visibility across company boundaries and their respective IT systems. According to a study by the Fraunhofer Institute for Manufacturing Engineering and Automation IPA, 85 percent of the participants in the study see great added value in potential data sharing. The willingness to share data, however, is much lower at 73 percent. Skepticism is evident in aspects such as data protection.
An essential factor of the Control Tower is the recording of real-time data. Where is the order now? How much time is still needed until it reaches its destination? The Control Tower integrates track & trace solutions that record the entire transport process of the supply chain. This allows the entire transport process to be mapped transparently and the root causes of problems to be identified and resolved more easily. Depending on the Control Tower, there are additional functions such as alarm functions and analysis tools that supplement the basic functions.
Control Tower can be divided into the following categories according to their function:
Analytical Control Tower
The analytical Control Tower provides both a transparent overview of the supply chain and the necessary analytical tools as a basis for decision-making. In contrast to the Operational Control Tower, however, there is no possibility to implement solutions directly in the system.
Operational Control Tower
In an operational control tower, end-to-end processes are monitored and controlled. Based on real-time data, they enable not only to identify problems, but also to solve them in the system and carry out operational processes.
The path to an intelligent Control Tower
Artificial intelligence and associated methods such as machine learning and predictive analytics offer the possibility of increasingly automating processes - even in the control tower. Experts assume that supply chains will be completely digitalized in a few years' time by future technologies and will be able to operate increasingly autonomously and adaptively. AI technology goes beyond decision support. It includes decision making and autonomous control and can therefore automatically adapt to fluctuations in demand and supply.
How exactly does Machine Learning work?
Machine Learning, as a branch of Artificial Intelligence, can recognize patterns and algorithms in existing data sets and develop solutions based on them. For the software to learn independently, however, it requires not only a data set but also previously defined rules. In this way, for example, required stock levels can be automatically adjusted to fluctuations in demand.
Predictive Analytics & Prescriptive Analytics
Statistical procedures and analyses can be used to highlight the interrelationships of historical data and generate forecasts with the help of predictive analytics. On this basis, it is possible to identify opportunities and risks at an early stage and include them in the decision-making process. Prescriptive analytics goes one step further. Simulation models are used to compare decision options with each other and make recommendations for action. In the future, the Control Tower could use self-learning algorithms to better and better adapt and implement solutions independently.
How Will This Change the Workplace of the Future?
The impact of AI on the Supply Chain Control Tower could be significant. AI technology will allow for increasingly automated processes, enabling supply chains to operate more autonomously and adaptively. Machine learning and predictive analytics will enable the Control Tower to recognize patterns, generate forecasts, and identify opportunities and risks at an early stage. This will allow supply chain managers to make more informed decisions and improve the efficiency of their operations.
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